Automated listing management

ABSTRACT

Disclosed is a sales system for lots of items that includes business rule definition logic. The sales system also includes offering creation logic that is operative to dynamically create different offerings for items in the lots. The offering creation logic optimizes return based on one or more of the business rules by using different offering parameter values for the different offerings.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No. 10/201,586 filed Jul. 22, 2002, which application claims the benefit under 35 U.S.C. 119(e) of U.S. Provisional Application No. 60/306,828 filed on Jul. 20, 2001, which applications are incorporated in their entirety herein by reference.

COPYRIGHT NOTICE

Portions of the disclosure of this patent document contain material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or patent disclosure as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever. Copyright FairMarket, Inc. 2001, 2002.

FIELD OF THE INVENTION

The invention relates to systems capable of managing surplus inventory, such as systems that optimize price for surplus goods or services.

BACKGROUND OF THE INVENTION

There are a variety of different types of network-based sales systems now in existence. A number of these implement the traditional English auction. This mechanism efficiently allocates individual lots by awarding them to the buyers who attribute the most value to them. But English auctions are not necessarily an optimum mechanism for selling larger quantities of goods, such as seasonal retail items, overstock, or discontinued merchandise, and these types of goods are therefore often sold using other types of electronic sales systems.

The simplest of these alternate systems strive to reproduce an in-store shopping experience in which goods are offered for sale at a particular non-negotiable markdown price. This approach requires sellers to gauge the demand for their products so that they can determine a price that is high enough to allow them an acceptable return, but not so high that few or no buyers will purchase them. This process can be difficult and time consuming, and may be too much so to be warranted for relatively small lots of goods. And setting a particular price can also allow some individuals who place a high value on an item to buy it for less than that value.

So-called Request-for-Proposal (RFP) systems allow buyers to place bids, which sellers can then choose to satisfy. These systems can allow sellers to provide the same goods to buyers who value them differently and thereby improve their profit levels. And although at least one system warns users against bids that are too low, such systems can be daunting to some buyers because they must thoroughly understand the value and demand for the item, or risk submitting bids that are too high.

Falling-price systems drop the price of goods over time until they are sold. Buyers can commit to buy early, or wait for a lower price at the risk of losing the item. At least one such system allows a user to pay a premium to place firm bids for later days using a so-called buyer's agent. Like RFP systems, falling-price systems can allow sellers to provide the same goods to buyers who value them differently. But they can also be daunting to some buyers, who must thoroughly understand the value and demand for the item, or risk submitting bids that are too high.

The network-based sales mechanisms described so far are by no means the only ones currently available to buyers and sellers. Others include Dutch auctions, sealed bid auctions, and classifieds. But no single one of all of these different mechanisms appears to present an optimum solution for selling larger lots of goods, such as seasonal retail items, overstock, or discontinued merchandise.

SUMMARY OF THE INVENTION

In one general aspect, the invention features a sales system for lots of items that includes business rule definition logic. The sales system also includes offering creation logic that is operative to dynamically create different offerings for items in the lots. The offering creation logic optimizes return based on one or more of the business rules by using different offering parameter values for the different offerings.

In preferred embodiments, the business rule definition logic can be operative to define rules based on a target cost recovery rate. The business rule definition logic can be responsive to user business rule creation commands. The offering creation logic can be operative to optimize return by adjusting lot price. The offering creation logic can be operative to optimize return by adjusting lot quantity. The offering creation logic can be operative to create offerings for a plurality of sales channels. The offering creation logic can be operative to adjust offerings on one of the sales channels based on results from another of the sales channels. The business rule definition logic can be operative to create rules that are dependent on results from prior offerings. The business rule definition logic can be operative to create rules that are dependent on margins from prior offerings. The price offering creation logic can be operative to create a series of auctions based on parameters determined by results from previous auctions. The business rule definition logic can be operative to create offerings based on absolute or relative amounts. The business rule definition logic can employ a web-based interface. The business rules can be set on a SKU, category, and site level. The system can further include default sales parameter creation logic operative to set sales parameters for the offerings. The sales parameter creation logic can be operative to set bidding parameters for an auction. The price offering creation logic can use exponential smoothing to derive parameters for the price offerings. The system can further include search logic operative to search for items in the lots. The system can further include falling price default logic operative to create fixed default falling price parameters. The system can further include scheduled allocation logic operative to create a scheduled set of offerings with predetermined parameters. The system can further include item display logic operative to display information about items in each of the lots with controls that allow the user to access the business rule definition logic for the item in the lot for which information is displayed. The system can further include a forecasting report generator operative to produce a report that forecasts future operation of the offering creation logic.

In another general aspect, the invention features a sales system for lots of items that includes means for defining machine-readable business rules and means for automatically creating a plurality of different offerings for items in the lots based on the machine-readable business rules defined by the means for defining. The means for automatically creating optimizes return based the machine-readable business rules defined by the means for defining using different offering parameter values for the different offerings.

In a further general aspect, the invention features a method of selling lots of items that includes defining machine-readable business rules and automatically creating a plurality of different offerings for items in the lots based on the machine-readable business rules. The step of automatically creating optimizes return based on the machine-readable business rules defined in the step of defining using different offering parameter values for the different offerings. Systems according to the invention can be beneficial in that they allow for the creation of rules that can be used to automatically liquidate lots of items. Once the rules are created, the user does not need to monitor the liquidation process any further. This makes the task of liquidating items more cost-effective than a manual approach might be. And rules may even perform better than would a human defining listings based on his or her subjective judgments.

DESCRIPTION OF THE DRAWING

FIG. 1 is a block diagram generally illustrating the operation of an illustrative embodiment of a Surplus Inventory Management System (SIMS) according to the invention;

FIG. 2 is diagram illustrating an item or product page for the SIMS of FIG. 1;

FIG. 3 is a diagram illustrating a defaults page for the SIMS of FIG. 1;

FIG. 4 is a diagram illustrating a services page for the SIMS of FIG. 1;

FIG. 5 is a diagram illustrating a search page for the SIMS of FIG. 1;

FIG. 6 is an illustrative plot of listing quantity against listing history for the SIMS of FIG. 1;

FIG. 7 is a diagram illustrating a business rules default page for the SIMS of FIG. 1;

FIG. 8 is a diagram illustrating a business rules page for the SIMS of FIG. 1;

FIG. 9 is a diagram illustrating an override control for the SIMS of FIG. 1;

FIG. 10 is a diagram illustrating a reporting page for the SIMS of FIG. 1;

FIG. 11 is a diagram illustrating an item page for an another embodiment of the SIMS system of FIG. 1;

FIG. 12 is a diagram illustrating a scheduled allocation page for the SIMS of FIG. 11;

FIG. 13 is a diagram illustrating an item page for the SIMS of FIG. 11;

FIG. 14 is a diagram illustrating an automatic listing settings page for the SIMS of FIG. 11;

FIG. 15 is a diagram illustrating an item or product editing page for the SIMS of FIG. 11; and

FIG. 16 is a diagram illustrating a rules report page for the SIMS of FIG. 11.

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

A Surplus Inventory Management System (SIMS) according to the invention is a logic driven re-listing and inventory management engine designed to handle all or some portion of the customer's excess inventory. It operates generally according to FIG. 1. SKU, pricing, images and copy are first extracted 14 from client databases 10, 12 into extract files 16 that allow product information to be uploaded into the SIMS 20. Offerings are created and distributed 22 based on the SIMS and can be sent to a sales site, such as an auction site 24. Fulfillment information can then be extracted and used to update the SIMS and user and product information can be transferred to the client database 12. Cost recovery parameters can be managed separately 30 though the SIMS.

The SIMS preferably should allow one or more customers to allocate surplus inventory into a centralized database that automatically relists items into an auction system, which can be run by an auction service provider, based up a set of predefined business rules. Suitable auction functionality is described in “Publishing System for Network-Based Sales,” filed Nov. 16, 1999, issued Ser. No. 09/441,385, which is the basis for published PCT application no. PCT/US00/31542, entitled “Network-Based Sales System,” filed Nov. 16, 2000, which are both herein incorporated by reference.

The SIMS preferably provides real-time reports and audits of upcoming listings as well as historical results of past listings. It also preferably displays a master scheduler report and exception report of all upcoming customer listings (quantity, retail value, predicted sell value) by category and date to help plan inventory allocation and forecast future revenue.

Listing flexibility is important for the SIMS since not all inventories may flow through the SIMS engine. Product data can be loaded into the SIMS database via text files, Microsoft Excel® files or an XML interface. A data validation procedure can ensure that the upload contains the proper fields and format. In this embodiment, the following fields are provided for:

Required Fields—Each Row Must Contain the Following

SKU—A unique identifier for each product

Category—Used to roll up aggregate data for reporting

Quantity Available—Number of units available per SKU

Cost Per Unit—Cost value per SKU

Format—Auction, Falling Price

Optional Fields—Data May be Excluded; Excluded Information Will Default to by Site or Category

Image Reference

Description

Target Cost Recovery Rate—Ideal price each SKU should achieve.

Starting Quantity—Default quantity of listing by SKU. Will allow for higher velocity of high inventory items.

Start Date

Starting Time

End Time

Bid Increment

Reserve Price

Rest Period—Days between Listing

Listing Logic—Allows the customer to override business rules and move listings out in a linear fashion rather than iterating demand curve.

Fixed Quantity—If business rules are overridden this field will dictate the number of items in each listing.

Referring to FIG. 2, in addition to mass upload, a Hypertext Markup Language (HTML) interface can allow for manipulation by SKU. The HTML interface can provide (see also item page 34):

New SKU and Inventory combination

Updating Previous SKU and Inventory

Search

Add

Delete

Edit

In addition to auctions, the SIMS can support listings in other pricing formats. For example, referring to FIG. 3, the SIMS can logically allocate inventories using a falling price auction model (“plunging prices”) by using the format variable. The business rules can work in the same manner as auctions. The SIMS can control the reserve price and quantity dependent on margins.

No additional information is required for these channels except for predefined defaults. There can be a separate screen 36 to capture this default information. To increase upload efficiency, plunging price variables can be derived from auction variables and the default settings. This way, items can move between channels with the change of just the format parameter.

Fixed price listings can be managed through the same process. The fixed price listing can be priced at some percent of cost and applied at the SKU, category, or site level. This channel can also be open to use other systems, such as a demand based pricing engine described in “Sales System With Sales Activity Feedback,” Ser. No. 09/686,073, and “Sales System With Buyer Price Selection,” Ser. No. 09/685,449, both filed on Oct. 11, 2000 and herein incorporated by reference.

Referring again to FIG. 1, the SIMS can also have the ability to automatically move inventory into other channels 32 such as another web auction provider or B2B channels. The customer can have the same fulfillment process with the SIMS as before. The SIMS can use that current report to allocate/de-allocate inventory. No additional work is needed to fulfill based on the SIMS listings.

The SIMS can have scheduling reports that forecast future lots, quantities and sales based on the most current information. For example, a lot of 100 camcorders that have a duration of one week, and assuming movement of 10 units a week, would show 10 lots of quantity 10 for the next ten weeks with the corresponding sales forecast. This should help the customer plan and schedule inventory more efficiently.

Referring to FIG. 4, the customer can interact with the SIMS via an administrative back end that is also used for auctions, but also includes an additional professional services link. Alternatively, the functionality could be provided in a dedicated software product. The administrative back end can provide a services page 38 that includes links for the SIMS, including a mass upload link, a search link, a reporting link, and a manage business rules link.

Referring to FIG. 5, the customer can search for SIMS listings with a search page 40 using the following criteria:

SKU

Quantity Available

Creation Date

Category

Target Cost Recovery Rate

Title

Each SKU can be editable in real-time by the following criteria:

Quantity Available

Target Cost Recovery

Start Time

End Time

Bid Increment

Rest Period

Pricing Format

Open listings may not be modified expect in standard methods (close a listing, description edits).

The rules engine can be set at the site, category or SKU level. Defaults will be set by the same level structure such that any omitted field in the business logic will default to the next highest level. For example, if the target cost recovery rate is omitted for a Panasonic camcorder, it will default to electronics' cost recovery rate. If that is omitted, it will default to the site cost recovery rates. All business rules will have the same default logic resulting in rules that are as specific as necessary.

Referring to FIG. 6, two modes are available. In a first mode (mode one), cost recovery of last listing will be used (see e.g., curve 42). In a second mode (mode two), exponential smoothing may be used if necessary (see, e.g., curve 44). Exponential smoothing eliminates the relative peaks and valleys of demands. It works by weighting past results with different coefficients to make less drastic changes in lot quantities.

A sample business objective could be to maximize total sales subject to inventory and a 50% cost-dollar recovery rate. This objective could employ the following business rules:

Starting bid is always $1

List duration is always 4 days

Auctions always start at 1:00 AM (EST) and end at 10:00 PM (EST)

If cost recovery is greater than 50%, then increase quantity of the next listing by 1

If cost recovery is between 42-50%, then keep quantity of next listing constant

If cost recovery is less than 40%, then decrease quantity of next listing by 1

Based on the customer's empirical data of “8 pc. Venetian Scallop Towels-White,” for example, the SIMS could have produced the results shown in Tables 1 and 2.

TABLE 1 Quantity Item 1 2 3 8 pc. Venetian Scallop Towels - White 69.76% 51.03% 41.22%

TABLE 2 Step Input SIMS Action 1. Upload nine (9) 8 pc. Create a test listing of quantity 1. Venetian Scallop Allocate 1 unit to “reserve” status leaving Towels - White 8 units available in the SIMS. 2. Test listing closes for De-allocate 1 unit from “reserve” status, 69.76% cost recovery. since item is sold. Evaluate cost recovery rate. Based on business rules increase quantity to 2 units. Allocate 2 units to “reserve” status leaving 6 units available in the SIMS. Create a listing for Qty 2. 3. Listing close for De-allocate 2 units from “reserve” status 51.03% cost recovery Evaluate cost recovery rate. Increase quantity to 3 units. Allocate 3 units to “reserve” status leaving 3 units available in the SIMS. Create a listing for Qty 3. 4. Listing close for De-allocate 3 units from “reserve” status. 41.22% cost recovery Evaluate cost recovery rate. Keep quantity of 3. Allocate 3 units to “reserve” status leaving 0 units available in the SIMS. Create a listing for Qty 3. 5. Listing close for De-allocate 3 units from “reserve” status. 41.22% cost recovery Evaluate cost recovery rate. Keep quantity of 3. Check available quantity. No More Quantity. Stop.

Referring to FIG. 7, the customer can control the following variables by static input (i.e., no logic need be used to derive the settings), at the SKU, category, and site level, using a business rules default page 46.

Opening Time (Hour/Min)

Closing Time (Hour/Min)

Bid Increment

Opening Bid

Duration (Days)

Rest Period

Referring to FIG. 8, logic rules may be based on a set quantity and margin relationship using a business rules page 48. The logic can be set at the SKU, category, or site level. Depending on the margin of one or more previous listings, the size of the next lot will change by either an absolute number or a relative percentage.

In order to maintain control over inventory, a stop rule can allow the customer to stipulate a condition where no more listings will be placed by the SIMS. The system can report on these items individually. The stop rule should work under at least the following conditions: stop at predetermined quantity, stop at target recovery rate, stop on predetermined date. This feature is designed to help eliminate poor performing inventory. These items may then be moved from the SIMS and liquidated at $0.30 on the cost dollar. Stop logic may be implemented to work at the site level only.

Referring to FIG. 9, in the event that a customer decides to move items out at certain velocity regardless of margins, the auction service provider can provide override (linear quantity) functionality, which can be accessed through an override control 50. For example, if there are 10,000 SKUs, the customer may simply list 500 item lots over the next 20 weeks at a default duration of one week each.

Referring to FIG. 10, to maintain the integrity of the SIMS both daily audit reports and customer request reports can be made available, such as through a reporting page 52. Daily reports can be available by SKU, category, and site that detail the performance of previous day's closing items. When the logic engine evaluates the next set of listing quantities, the margins should be stored in a flat file that can be rolled up by category and site. An example report is shown in Table 3.

TABLE 3 Cost Recovery By Category By Day Base Category 6/1 6/2 6/3 6/4 6/5 6/6 6/7 6/8 6/9 6/10 Total Books 51% 50% 49% 48% 45% 50% 51% 60% 50% 52% 51% computer 51% 51% 50% 49% 48% 45% 50% 51% 60% 50% 51% Seasonal 49% 51% 52% 48% 56% 50% 51% 51% 52% 42% 50% Apparel- 51% 51% 50% 49% 48% 45% 50% 51% 60% 50% 51% accessories Home 49% 51% 52% 48% 56% 50% 51% 51% 52% 42% 50% assortment Auto- 51% 51% 50% 49% 48% 45% 50% 51% 60% 50% 51% hardware electronics 49% 51% 52% 48% 56% 50% 51% 51% 52% 42% 50% Toys 51% 51% 50% 49% 48% 45% 50% 51% 60% 50% 51% Office 49% 51% 52% 48% 56% 50% 51% 51% 52% 42% 50% Sports- 51% 51% 50% 49% 48% 45% 50% 51% 60% 50% 51% outdoors b2b- 54% 51% 52% 48% 56% 50% 51% 51% 52% 42% 51% business Grand 51% 51% 51% 48% 51% 48% 51% 52% 55% 47% 50% Total (All dates in 2001)

Exception reports can also be made available. This type of report will display the numbers of available items each day to help manage site breadth (see Table 4). It can work by evaluating current inventory levels, the current velocity of that inventory, and forecasting item sales with the most recent information. This evaluation can be governed by the following relationships.

Number of Listings Remaining=Current Inventory/Current Lot Size

Expected Sell Out Date=Number Of Listings Remaining*(Duration+Rest Period)+Today's Date

TABLE 4 Item Open Per Day Base Category 6/1 6/2 6/3 6/4 6/5 6/6 6/7 6/8 6/9 6/10 Total Books 12 17 20 21 18 19 20 23 16 15 181 computers 16 14 15 17 20 21 18 19 20 23 183 seasonal 15 17 20 21 18 19 20 23 16 14 183 Apparel- 14 17 20 21 18 19 20 23 16 22 190 accessories home 21 24 29 30 26 27 29 33 23 21 263 assortment auto- 14 13 17 20 21 18 19 20 23 16 181 hardware electronics 20 22 26 27 23 25 26 30 21 20 239 Toys 15 17 20 21 18 19 20 23 16 15 184 Office 12 15 17 20 21 18 15 17 20 21 176 sports- 12 9 17 20 21 18 19 20 23 16 175 outdoors b2b- 17 20 21 18 19 20 23 16 13 10 177 business Grand 168 185 222 236 223 223 229 247 207 193 2,132 Total (All dates in 2001)

A sales forecasting report can be made available as well (see Table 5). Based on the exception report and the margin reports, the sales forecast report can give estimates of future sales by category given current recovery rates and inventory supplies. This evaluation can be governed by the following relationship.

Forecast Sales=Audit Report*Exception Report*Average Cost by Category

TABLE 5 Forecasted Sales (Based on Past Recovery History) Base Category 6/1 6/2 6/3 6/4 6/5 6/6 6/7 6/8 6/9 6/10 Total Books 54 77 90 95 81 86 90 104 72 68 815 computers 10000 8750 9375 10625 12500 13125 11250 11875 12500 14375 114375 Seasonal 525 595 700 735 630 665 700 805 560 490 6405 apparel- 364 442 520 546 468 494 520 598 416 572 4940 accessories home 965 1094 1287 1351 1158 1223 1287 1480 1030 965 11840 assortment auto- 1470 1365 1785 2100 2205 1890 1995 2100 2415 1680 19005 hardware Electronics 2243 2542 2990 3140 2691 2841 2990 3439 2392 2243 27508 toys 315 357 420 441 378 399 420 483 336 315 3864 office 2400 3000 3400 4000 4200 3600 3000 3400 4000 4200 35200 sports- 1020 765 1445 1700 1785 1530 1615 1700 1955 1360 14875 outdoors b2b- 3825 4500 4725 4050 4275 4500 5175 3600 2925 2250 39825 business Grand 23181 23486 26737 28782 30371 30352 29042 29583 28601 28517 278652 Total (All dates in 2001, all amounts in dollars)

Referring to FIG. 11, an alternative illustrative embodiment of a SIMS includes a product listing rule page 54 that can be reached through the item page and allows users to select between three types of rules. The first type is an unspecified type, which allows the item to be treated according to default site or category rules. The second type is a scheduled allocation type, which allows the user to reach a scheduled allocation rule page 56. The third is a price optimization type, which can operate in much the same way as is presented above in connection with the embodiment of FIGS. 1-10.

Referring to FIG. 12, the scheduled allocation page 56 includes a channel selection control 58, which enables a user to select a channel for which the rule is to be edited. This control can allow different rules to be created to operate simultaneously for different channels. Using this control, a user can therefore simultaneously try to sell different numbers of items through different channels, using mode 1, mode 2, or a combination of the two. For example, the user can attempt to sell a large number of items though its own web site using a price optimization rule and attempt to sell smaller quantities through third party systems using scheduled allocation rule.

Feedback can be provided within a channel and/or between channels. If listings on a first channel stop doing well, for example, the SIMS can reduce the lot size on that channel and increase it on one or more other channels. For instance, a user could create a rule that would cause listings to be generated on a home site for 20 days, and then cause the remaining inventory to be liquidated through an auction provider.

The scheduled allocation page includes a number of additional controls to specify scheduled allocation parameters, such as a listing type text box, start and end text boxes, a duration text box, a rest period text box, a reserve price text box, an initial price text box, and an initial quantity text box. A compound stop control is also provided to specify a stop condition. Using the scheduled allocation page, a user can, for example, create a series of weekly eight-hour auction listings with identical predetermined opening and reserve prices, with listings being posted until all product is sold out. Although this type of liquidation schedule does not exhibit performance feedback, it is believed to provide a straightforward and useful way to schedule the liquidation of some types of lots of items.

Referring to FIG. 13, an item page 60 in this embodiment includes product information and a number of controls. These controls include a compound listing placement control 62 with a channel selection control and a submit button. The listing placement control allows the user to simply list one or more items through one of the channels.

Referring also to FIG. 14, an edit automatic listing settings link 64 in the item page 60 can lead the user to an automatic listings settings page 68. This page can allow users to reset or disable automatic rules for an item. Resetting the automatic rules will cause the system to ignore any previously-created listings the next time an automatic rule creates a listing for the item. This allows the item to start fresh with initial price settings rather than basing its price on a past price history. Disabling rules prevents listings from being created automatically, but does not delete item-level rules. The user can therefore undo this command to reinstate an automatic rule.

Referring also to FIG. 15, an edit item button 66 on the item page 60 can lead the user to an item edit page 70. This page includes a number of controls that allow the user to provide information about the item. This information can include item description items and sales parameters. The item description items can include a product name, an item number/SKU, an image location, a shipping weight, and a description. The sales parameters can include the quantity available, the retail price, the cost, and the target recovery rate. The sales parameters can also include default auction durations, start prices and bid increments.

Referring to FIG. 16, a rules report can be used to summarize all of the rules for a series of items. This report can include links to the item pages and to the corresponding rules for those pages. Links can also be provided to a site listing rule page that allows the default site listing rule type to be set to use price optimization rules or scheduled allocation rules.

In the embodiment presented, users interact with the server via hypertext transfer protocol (HTTP) over the span of one or more network connections. But numerous other platform technologies could be used to implement part or all of the system, such as dedicated hardware devices or simpler programmable devices interconnected by wireless or analog networks. Connections between elements can be intermittent (e.g., e-mail connections) or indirect. The function and structure of the various elements shown can also be broken down in different ways than those shown in figures, with logic elements being combined, separated, or recast as appropriate. And while the system's user interface is based on software-based graphical user interface elements, these could be readily rearranged in a variety of ways, and the user interface could even include other implementation elements, such as physically actuated controls or auditory prompts. In addition, while the system's user interface elements are presented as displayed in pages, one of ordinary skill in the art would recognize that they could also be displayed in other types of display regions, such as screens, cards, or windows. And while the system is useful in liquidating surplus product inventory, it can also be used for other types of transactions for a variety of types of items, such as services or even intangible items.

The present invention has now been described in connection with a number of specific embodiments thereof. However, numerous modifications which are contemplated as falling within the scope of the present invention should now be apparent to those skilled in the art. It is therefore intended that the scope of the present invention be limited only by the scope of the claims appended hereto. In addition, the order of presentation of the claims should not be construed to limit the scope of any particular term in the claims. 

1. A system, comprising: one or more servers to execute: business rule definition logic to define at least one business rule; and offering creation logic to dynamically create a plurality of different listings on a network-based sales system, the plurality of different listings to respectively offer a lot that includes at least one item, the offering creation logic to optimize a financial return for the plurality of listings based on the at least one business rule that is operatively used to adjust offering values included in the respective listings, the offering creation logic is to adjust an offering parameter value in a second listing based on sales results of a first listing.
 2. The system of claim 1, wherein the offering parameter value is a second offering value.
 3. The system of claim 1, wherein the offering parameter value is a second offering quantity.
 4. The system of claim 1, wherein the business rule definition logic is to define the at least one business rule based on an optimal price for each of the at least one items, wherein the plurality of listings is associated with a plurality of items, and wherein the optimal price for each of the at least one items is configured as a target cost recovery rate that is a percentage of a cost for each of the at least one items.
 5. The system of claim 1, wherein the second listing is created for a second sales channel based the first listing that is created for a first sales channel.
 6. The system of claim 1, wherein the business rule definition logic is to create the at least one business rule based on results from prior listings.
 7. The system of claim 6, wherein the results from prior listings includes financial margins from prior listings.
 8. The system of claim 1, further including default sales parameter creation logic to set sales parameters for the offerings.
 9. The system of claim 8, wherein the sales parameter creation logic is to set bidding parameters for an auction.
 10. The system of claim 1, wherein the price offering creation logic uses exponential smoothing to derive parameters for the price offerings.
 11. The system of claim 1, further including falling price default logic to create fixed default falling price parameters.
 12. The system of claim 1, further including a forecasting report generator to produce a report that forecasts future operation of the offering creation logic.
 13. A method of selling items in lots, comprising: defining, by one or more servers, machine-readable business rules; and automatically creating a plurality of different offerings for one or more items in the lots based on the machine-readable business rules, the automatically creating optimizing return based on the machine-readable business rules using different offering parameter values for the different offerings.
 14. The method of claim 13, further comprising adjusting an offering parameter value in a second listing based on sales results of a first listing.
 15. The method of claim 14, wherein the offering parameter value is a second offering value.
 16. The method of claim 14, wherein the offering parameter value is a second offering quantity.
 17. The method of claim 13, wherein the optimizing return is based on a target cost recovery rate that is a percentage of a cost for each item in each lot.
 18. The method of claim 13, wherein defining the machine-readable business rules is based on results from prior listings.
 19. The method of claim 13, wherein the automatically creating comprises using exponential smoothing to derive parameters for the different offerings.
 20. The method of claim 13, further comprising creating fixed default falling price parameters. 